Can anyone explain me in simple language what is PSM, PEP score and unique peptide no. in analysis result of Protein LC/MS-MS data? and what should be the cut off value of that to say an identified protein to be the good match?
Hi Shraddha,
# Unique peptides
The number of peptide sequences unique to a protein group.
# Peptides
The number of distinct peptide sequences in the protein group. This can be different from unique peptides if the peptide sequence appears identically in another protein within the proteome.
# PSMs
The total number of identified peptide sequences (peptide spectrum matches) for the protein, including those redundantly identified (peptides can be “seen” more than once in a run). The higher the better.
Posterior Error Probability (PEP)
The posterior error probability (PEP) is the probability that the observed PSM is incorrect. Ideally, you want this to be low. The more unique peptides and PSMs, the greater the confidence you can have, generally speaking.
Here is a link to an excellent review on the subject matter:
Article Posterior Error Probabilities and False Discovery Rates: Two...
Additionally, here is a link to Thermo's Proteome Discoverer v 2.2 analysis software that may be able to assist you further:
https://assets.thermofisher.com/TFS-Assets/CMD/manuals/Man-XCALI-97808-Proteome-Discoverer-User-ManXCALI97808-EN.pdf
I hope this helps,
Jarrod
Hi Shraddha,
# Unique peptides
The number of peptide sequences unique to a protein group.
# Peptides
The number of distinct peptide sequences in the protein group. This can be different from unique peptides if the peptide sequence appears identically in another protein within the proteome.
# PSMs
The total number of identified peptide sequences (peptide spectrum matches) for the protein, including those redundantly identified (peptides can be “seen” more than once in a run). The higher the better.
Posterior Error Probability (PEP)
The posterior error probability (PEP) is the probability that the observed PSM is incorrect. Ideally, you want this to be low. The more unique peptides and PSMs, the greater the confidence you can have, generally speaking.
Here is a link to an excellent review on the subject matter:
Article Posterior Error Probabilities and False Discovery Rates: Two...
Additionally, here is a link to Thermo's Proteome Discoverer v 2.2 analysis software that may be able to assist you further:
https://assets.thermofisher.com/TFS-Assets/CMD/manuals/Man-XCALI-97808-Proteome-Discoverer-User-ManXCALI97808-EN.pdf
I hope this helps,
Jarrod
Thank You so much for very nice explanation. I found all statistical definitions very difficult to understand. I still little confused with PEP score as some people suggested the PEP score should be higher in order to be the best matched protein or may me PEP score and probabilities are two different things that I am assuming to be same.
I also thank you for providing software link and article.
Hi Shraddha,
Very happy to oblige! You definitely do not want a high pep score. Do you by chance have a Sequest-HT or Xcorr score on your dataset?
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